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The GFDL-CM4X climate model hierarchy, Part II: case studies
This paper is Part II of a two-part paper that documents the CM4X (Climate Model version 4X) hierarchy of coupled climate models …
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Generalizable neural-network parameterization of mesoscale eddies in idealized and global ocean models
Data-driven methods have become popular to parameterize the effects of mesoscale eddies in ocean models. However, they perform poorly …
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Controls on the ocean response to idealized Antarctic meltwater input
Antarctic meltwater is expected to increase throughout the coming centuries and impact sea level, ocean circulation, and the coupled …
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The Impact of Natural External Forcing on Ocean Heat Uptake Efficiency Since the 1980s
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A landscape of mesoscale eddy vertical structure: the influence of bathymetric slope and roughness on kinetic energy
Surface and upper ocean measurements of mesoscale eddies have revealed the central role they play in ocean transport, but their …
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A theory for how the depth of meltwater injection impacts regional sea level evolution
Mass loss from the Antarctic ice sheet is projected to continue over the coming century. The resultant sea level change will have a …
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A fluctuation-dissipation theorem perspective on radiative responses to temperature perturbations
Radiative forcing drives warming in the Earth system, leading to changes in sea surface temperatures (SSTs) and associated radiative …
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Observational constraints imply limited future Atlantic meridional overturning circulation weakening
The degree to which the Atlantic meridional overturning circulation (AMOC) weakens over the twenty-first century varies widely across …
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Design and implementation of a data-driven parameterization for mesoscale thickness fluxes
Mesoscale eddies are a major sink of available potential energy (APE) in the ocean. When these eddies are not resolved or only …
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Addressing Out-of-Sample Issues in Multi-Layer Convolutional Neural-Network Parameterization of Mesoscale Eddies Applied Near Coastlines
This study addresses the boundary artifacts in machine-learned (ML) parameterizations for ocean subgrid mesoscale momentum forcing, as …
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